An Insight into Codon Pattern Analysis of Autophagy Genes Associated with Virus Infection

Author:

Singhal Shailja1,Kumar Utsang1,Alqahtani Taha2,Rzhepakovsky Igor Vladimirovich3,Khandia Rekha1,Pandey Megha4,Alqahtani Saud2,Alharbi Hanan5,Kamal Mohammad Amjad6789

Affiliation:

1. Department of Biochemistry and Genetics, Barkatullah University, Bhopal, 462026, India

2. Department of Pharmacology, College of Pharmacy, King Khalid University, Abha, 62529, Saudi Arabia

3. Medical and Biological Faculty, North Caucasus Federal University, Stavropol, Russia

4. Translational Medicine Center, All India Institute of Medical Sciences, Bhopal, 462020, India

5. Department of Pharmaceutics, College of Pharmacy, Umm Al-Qura University, Makkah, 21955, Saudi Arabia

6. Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, China

7. King Fahd Medical Research Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

8. Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Dhaka, 1207, Bangladesh

9. Enzymoics, Novel Global Community Educational Foundation, 7 Peterlee place, Hebersham, NSW 2770, Australia

Abstract

Introduction: Apoptosis and autophagy are the two fundamental processes involved in maintaining homeostasis, and a common stimulus may initiate the processes. Autophagy has been implicated in various diseases, including viral infections. Genetic manipulations leading to altered gene expression might be a strategy to check virus infection. Aim: Determination of molecular patterns, relative synonymous codon usage, codon preference, codon bias, codon pair bias, and rare codons so that genetic manipulation of autophagy genes may be done to curb viral infection. Method: Using various software, algorithms, and statistical analysis, insights into codon patterns were obtained. A total of 41 autophagy genes were envisaged as they are involved in virus infection. Results: The A/T and G/C ending codons are preferred by different genes. AAA-GAA and CAG-CTG codon pairs are the most abundant codon pairs. CGA, TCG, CCG, and GCG are rarely used codons. Conclusion: The information generated in the present study helps manipulate the gene expression level of virus infection-associated autophagy genes through gene modification tools like CRISPR. Codon deoptimization for reducing while codon pair optimization for enhancing is efficacious for HO-1 gene expression.

Funder

Deanship of Scientific Research at King Khalid University

Publisher

Bentham Science Publishers Ltd.

Subject

Drug Discovery,Pharmacology

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